This latest Opinion piece is by Gareth Williams, CEO of Yellow Dog, and it looks at how technology can offer everyone in the insurance industry a better understanding of the risks posed by climate change.
2019 has been no stranger to extreme climate events. Whether that was the flash floods that devastated towns and cities across Europe in May, June, September and most recently in November in the UK, or the summer heatwave that broke records for the hottest July day ever on record in the UK (38.1C in Cambridge), these are turbulent times. Met Office data revealed that in the UK, the top ten highest temperatures on record have occurred since 2002. Some forecasters are predicting that the end of 2019 is set to bring some of the heaviest snowfall the UK has ever seen, along with the coldest days on record.
The rise of extreme weather events
In the wake of the Extinction Rebellion demonstrations it’s no secret that we are in a period of intense climate change. Experts say that heatwaves and other extreme weather events will continue – and indeed will be more likely – in the future. Indeed, earlier this year, the World Economic Forum (WEF) published its World Risks Report, concluding that the number one risk to the world was the failure of climate change mitigation and adaptation. With this in mind, some are calling for the insurance industry to look more closely at risk modelling.
The need for risk modelling
Risk-modelling and catastrophe-modelling is more pertinent than ever. The impact on the economy, and in particular the insurance industry, is huge when an unpredicted weather event occurs. The urgency for insurers to more accurately predict when these events will occur, and what the impact of them will be, is here and now.
The role of technology in risk modelling
With the immediacy and severity of climate change increasing, technology needs to be adopted far quicker to better predict when these events will occur and understand the consequences. Scenario modelling can help with extreme weather-related risk management. This type of predictive data technology helps to forecast the impact of various extreme weather scenarios including flooding, wildfires, and hurricanes to allow for planning, mitigation, and full preparation for the financial implications of climate change events.
Weather simulations can establish an insurer’s exposure to certain risks. They help insurers look ahead to increase accuracy and confidence in insuring a specific client or industry; or retrospectively they help insurers to analyse their financial positions as a result of particular weather events. One example of this is the large predictive models that are in use in California to help predict the wind direction and the path of the wildfires. Government and insurers watch this weather modelling to help save the lives and property of Californian residents who may be at risk.
Closer to home, UK insurance industry body ABI reports that inland flooding would have cost almost three times more without flood defences – or a bill of £1.8 billion rather than the £0.7 billion it costs to build and maintain these defences. The Environment Agency recently recommended an annual spend of £1 billion on this sort of flood risk management – these figures should be largely based on simulations and models that compare necessary investments, like flood defences, against the possible losses.
When forecasting weather patterns, intelligent satellites measure changes in airflow and temperature. Simulating what happens next is more complex. The impact of weather – like the floods across the North of the UK – is affected by known data sets such as soil density, altitude, and pressure. The more data an enterprise has access to, the greater the level of confidence in accuracy. However, this fast and accurate data processing requires huge amounts of computing power. Moreover, whilst a huge amount of computing power is required to calculate these simulations, it can be dwarfed by the computing power then required to calculate the correlating impact on insurers.
There is reason to be optimistic; with more computing power at our disposal, more scenarios can be generated. More scenarios can be planned for. For example, insurance companies could benefit as they search for ever increasing detail and iterations.
This will impact the downstream services in the insurance industry too. Brokers will play a more important role in sharing advice with their clients on how to avoid the impact of changing weather conditions. They need to be armed with the correct information and this is where accurate modelling will help. Specialist brokers empowered with the right type of information will be able to better inform clients in terms of where they store or place their assets, such as property.
Similarly, we could see underwriters becoming less tolerant of businesses that ignore their own impact on climate change and don’t make an effort to be part of the solution. Brokers will increasingly be required to assist clients in identifying how their operations are impacting the climate. As the insurance industry becomes more informed, their clients will become better informed too.
Insurance is ultimately about predictability and understanding risk. Extreme weather conditions are set to continue. They will have direct knock on effects to consumers if insurers don’t have confidence in their own profitability. For the sake of business insurance and the economy at large, it is critical that we build a clear picture of the future as quickly as possible.
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